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pro vyhledávání: '"HU, Feifang"'
Publikováno v:
In Journal of Econometrics June 2024
Publikováno v:
Statistical Methods in Medical Research 30, no. 9 (2021): 2148-2164
Concerns have been expressed over the validity of statistical inference under covariate-adaptive randomization despite the extensive use in clinical trials. In the literature, the inferential properties under covariate-adaptive randomization have bee
Externí odkaz:
http://arxiv.org/abs/2009.04136
Network data have appeared frequently in recent research. For example, in comparing the effects of different types of treatment, network models have been proposed to improve the quality of estimation and hypothesis testing. In this paper, we focus on
Externí odkaz:
http://arxiv.org/abs/2009.01273
A/B testing is an important decision-making tool in product development for evaluating user engagement or satisfaction from a new service, feature or product. The goal of A/B testing is to estimate the average treatment effects (ATE) of a new change,
Externí odkaz:
http://arxiv.org/abs/2008.08648
Autor:
Hu, Feifang, Zhang, Li-Xin
Pocock and Simon's marginal procedure (Pocock and Simon, 1975) is often implemented forbalancing treatment allocation over influential covariates in clinical trials. However, the theoretical properties of Pocock and Simion's procedure have remained l
Externí odkaz:
http://arxiv.org/abs/2004.02994
Akademický článek
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Publikováno v:
In Computational Statistics and Data Analysis March 2023 179
Publikováno v:
Journal of the American Statistical Association 115, no. 531 (2020): 1488-1497
Covariate-adaptive randomization (CAR) procedures are frequently used in comparative studies to increase the covariate balance across treatment groups. However, because randomization inevitably uses the covariate information when forming balanced tre
Externí odkaz:
http://arxiv.org/abs/1807.09678
Akademický článek
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